分析复联系列电影台词，看看每个英雄说得最多的词是什么

*library*(dplyr)
*library*(grid)
*library*(gridExtra)
*library*(ggplot2)
*library*(reshape2)
*library*(cowplot)
*library*(jpeg)
*library*(extrafont)

rm(list = ls())

dir_images <- “C:\\Users\\Matt\\Documents\\R\\Avengers”
setwd(dir_images)

windowsFonts(Franklin=windowsFont(“Franklin Gothic Demi”))

character_names <- c("black_panther","black_widow","bucky","captain_america",
                     "falcon","hawkeye","hulk","iron_man",
                     "loki","nick_fury","rhodey","scarlet_witch",
                     "spiderman","thor","ultron","vision")
image_filenames <- paste0(character_names, ".jpg")

read_image <- *function*(filename){
  char_name <- gsub(pattern = "\\.jpg$", "", filename)
  img <- jpeg::readJPEG(filename)
  *return*(img)
}

all_images <- lapply(image_filenames, read_image)

names(all_images) <- character_names

/# clear the plot window/
grid.newpage()
/# draw to the plot window/
grid.draw(rasterGrob(all_images[[‘vision’]]))

capitalize <- Vectorize(*function*(string){
  substr(string,1,1) <- toupper(substr(string,1,1))
  *return*(string)
})

proper_noun_list <- c("clint","hydra","steve","tony",
                      "sam","stark","strucker","nat","natasha",
                      "hulk","tesseract", "vision",
                      "loki","avengers","rogers", "cap", "hill")

/# Run the capitalization function/
word_data <- word_data %>%
  mutate(word = ifelse(word %*in*% proper_noun_list, capitalize(word), word)) %>%
  mutate(word = ifelse(word == "jarvis", "JARVIS", word))

unique(word_data$Speaker)

##  [1] "Black Panther"   "Black Widow"     "Bucky"
##  [4] "Captain America" "Falcon"          "Hawkeye"
##  [7] "Hulk"            "Iron Man"        "Loki"
## [10] "Nick Fury"       "Rhodey"          "Scarlet Witch"
## [13] "Spiderman"       "Thor"            "Ultron"
## [16] "Vision"

character_labeler <- c(`black_panther` = "Black Panther",
                       `black_widow` = "Black Widow",
                       `bucky` = "Bucky",
                       `captain_america` = "Captain America",
                       `falcon` = "Falcon", `hawkeye` = "Hawkeye",
                       `hulk` = "Hulk", `iron_man` = "Iron Man",
                       `loki` = "Loki", `nick_fury` = "Nick Fury",
                       `rhodey` = "Rhodey",`scarlet_witch` ="Scarlet Witch",
                       `spiderman`="Spiderman", `thor`="Thor",
                       `ultron` ="Ultron", `vision` ="Vision")

convert_pretty_to_simple <- Vectorize(*function*(pretty_name){
  /# pretty_name = “Vision”/
  simple_name <- names(character_labeler)[character_labeler==pretty_name]
  /# simple_name <- as.vector(simple_name)/
  *return*(simple_name)
})
/# convert_pretty_to_simple(c(“Vision”,”Thor”))/
/# just for fun, the inverse of that function/
convert_simple_to_pretty <- *function*(simple_name){
  /# simple_name = “vision”/
  pretty_name <- character_labeler[simple_name] %>% as.vector()
  *return*(pretty_name)
}
/# example/
convert_simple_to_pretty(c(“vision”,”black_panther”))

## [1] “Vision”        “Black Panther”

word_data$character <- convert_pretty_to_simple(word_data$Speaker)

character_palette <- c(`black_panther` = “#51473E",
                       `black_widow` = "“#89B9CD"”
                       `bucky` = "“#6F7279"”
                       `captain_america` = "“#475D6A"”
                       `falcon` = "“#863C43", `hawkeye` = "#84707F",
                       `hulk` = “#5F5F3F", `iron_man` = "#9C2728",
                       `loki` = “#3D5C25", `nick_fury` = "#838E86",
                       `rhodey` = “#38454E",`scarlet_witch` ="#620E1B",
                       `spiderman`=“#A23A37", `thor`="#323D41",
                       `ultron` =“#64727D", `vision` ="#81414F" )

avengers_bar_plot <- word_data %>%
  group_by(Speaker) %>%
  top_n(5, amount) %>%
  ungroup() %>%
  mutate(word = reorder(word, amount)) %>%
  ggplot(aes(x = word, y = amount, fill = character))+
  geom_bar(stat = “identity”, show.legend = FALSE)+
  scale_fill_manual(values = character_palette)+
  scale_y_continuous(name =“Log Odds of Word”,
                     breaks = c(0,1,2)) +
  theme(text = element_text(family = “Franklin”),
        /# axis.title.x = element_text(size = rel(1.5)),/
        panel.grid = element_line(colour = NULL),
        panel.grid.major.y = element_blank(),
        panel.grid.minor = element_blank(),
        panel.background = element_rect(fill = “white”,
                                    colour = “white”))+
  /# theme(strip.text.x = element_text(size = rel(1.5)))+/
  xlab(“”)+
  coord_flip()+
  facet_wrap(~Speaker, scales = “free_y”)
avengers_bar_plot

max_amount <- max(word_data$amount)
word_data$remainder <- (max_amount - word_data$amount) + 0.2

word_data_top5 <- word_data %>%
  group_by(character) %>%
  arrange(desc(amount)) %>%
  slice(1:5) %>%
  ungroup()

word_data_top5_m <- melt(word_data_top5, measure.vars = c(“amount”,”remainder”))

word_data_top5_m$variable2 <- factor(word_data_top5_m$variable,
                                     levels = rev(levels(word_data_top5_m$variable)))

plot_char <- *function*(character_name){
  /# example: character_name = "black_panther"/
  /# plot details that we might want to fiddle with/
  /# thickness of lines between bars/
  bar_outline_size <- 0.5
  /# transparency of lines between bars/
  bar_outline_alpha <- 0.25
  /#/
  /# The function takes the simple character name,/
  /# but here, we convert it to the pretty name,/
  /# because we'll want to use that on the plot./
  pretty_character_name <- convert_simple_to_pretty(character_name)

  /# Get the image for this character,/
  /# from the list of all images./
  temp_image <- all_images[character_name]

  /# Make a data frame for only this character/
  temp_data <- word_data_top5_m %>%
    dplyr::filter(character == character_name) %>%
    mutate(character = character_name)

  /# order the words by frequency/
  /# First, make an ordered vector of the most common words/
  /# for this character/
    ordered_words <- temp_data %>%
      mutate(word = as.character(word)) %>%
      dplyr::filter(variable == "amount") %>%
      arrange(value) %>%
      `[[`(., "word")

    /# order the words in a factor,/
    /# so that they plot in this order,/
    /# rather than alphabetical order/
    temp_data$word = factor(temp_data$word, levels = ordered_words)

  /# Get the max value,/
  /# so that the image scales out to the end of the longest bar/
  max_value <- max(temp_data$value)
  fill_colors <- c(`remainder` = "white", `value` = "white")

  /# Make a grid object out of the character's image/
  character_image <- rasterGrob(all_images[[character_name]],
                                width = unit(1,"npc"),
                                height = unit(1,"npc"))

  /# make the plot for this character/
  output_plot <- ggplot(temp_data)+
    aes(x = word, y = value, fill = variable2)+
    /# add image/
    /# draw it completely bottom to top (x),/
    /# and completely from left to the the maximum log-odds value (y)/
    /# note that x and y are flipped here,/
    /# in prep for the coord_flip()/
    annotation_custom(character_image,
                      xmin = -Inf, xmax = Inf, ymin = 0, ymax = max_value) +
    geom_bar(stat = "identity", color = alpha("white", bar_outline_alpha),
             size = bar_outline_size, width = 1)+
    scale_fill_manual(values = fill_colors)+
    theme_classic()+
    coord_flip(expand = FALSE)+
    /# use a facet strip,/
    /# to serve as a title, but with color/
    facet_grid(. ~ character, labeller = labeller(character = character_labeler))+
    /# figure out color swatch for the facet strip fill/
    /# using character name to index the color palette/
    /# color= NA means there's no outline color./
    theme(strip.background = element_rect(fill = character_palette[character_name],
                                          color = NA))+
    /# other theme elements/
    theme(strip.text.x = element_text(size = rel(1.15), color = "white"),
          text = element_text(family = "Franklin"),
          legend.position = "none",
          panel.grid = element_blank(),
          axis.text.x = element_text(size = rel(0.8)))+
    /# omit the axis title for the individual plot,/
    /# because we'll have one for the entire ensemble/
    theme(axis.title = element_blank())
  *return*(output_plot)
}

plot_x_axis_text <- paste(“Tendency to use this word more than other characters do”,
                          “(units of log odds ratio)”, sep = “\n”)

sample_plot <- plot_char("black_panther")+
  theme(axis.title = element_text())+
  /# x lab is still declared as y lab/
  /# because of coord_flip()/
  ylab(plot_x_axis_text)
sample_plot

logit2prob <- *function*(logit){
  odds <- exp(logit)
  prob <- odds / (1 + odds)
  *return*(prob)
}

logit2prob(seq(0, 2.5, 0.5))

## [1] 0.5000000 0.6224593 0.7310586 0.8175745 0.8807971 0.9241418

diff(logit2prob(seq(0, 2.5, 0.5)))

## [1] 0.12245933 0.10859925 0.08651590 0.06322260 0.04334474

all_plots <- lapply(character_names, plot_char)

get_axis_grob <- *function*(plot_to_pick, which_axis){
  /# plot_to_pick <- sample_plot/
  tmp <- ggplot_gtable(ggplot_build(plot_to_pick))
  /# tmp$grobs/
  /# find the grob that looks like/
  /# it would be the x axis/
  axis_x_index <- which(sapply(tmp$grobs, *function*(x){
    /# for all the grobs,/
    /# return the index of the one/
    /# where you can find the text/
    /# "axis.title.x" or "axis.title.y"/
    /# based on input argument `which_axis`/
    grepl(paste0("axis.title.",which_axis), x)}
  ))
  axis_grob <- tmp$grobs[[axis_x_index]]
  *return*(axis_grob)
} 

px_axis_x <- get_axis_grob(sample_plot, “x”)
px_axis_y <- get_axis_grob(sample_plot, “y”) 

grid.newpage()
grid.draw(px_axis_x) 

/# grid.draw(px_axis_y)/

big_plot <- arrangeGrob(grobs = all_plots)

big_plot_w_x_axis_title <- arrangeGrob(big_plot,
                                       px_axis_x,
                                       heights = c(10,1))
grid.newpage()
grid.draw(big_plot_w_x_axis_title)

big_plot_aligned <- cowplot::plot_grid(plotlist = all_plots, align = 'v', nrow = 4)

big_plot_w_x_axis_title_aligned <- arrangeGrob(big_plot_aligned,
                                               px_axis_x,
                                               heights = c(10,1))

grid.newpage()
grid.draw(big_plot_w_x_axis_title_aligned)

ggsave(big_plot_w_x_axis_title_aligned,
       file = “Avengers_Word_Usage.png”,
       width = 12, height = 6.3)